> ## Documentation Index
> Fetch the complete documentation index at: https://docs.a1project.org/llms.txt
> Use this file to discover all available pages before exploring further.
# A1
> The agent-to-code compiler
## What is A1?
A1 is a direct replacement for agent frameworks. While prior art generates a static while loop program for each agent, an agent compiler generates a program optimized for each unique agent input.
## Why use an agent compiler?
1. **Safety** - Minimizes exposure of sensitive data to an LLM.
2. **Speed** - Up to 10x faster code generation.
3. **Determinism** - Code is optimized for minimal non-deterministic behavior (e.g. LLM calls replaced with code where possible).
4. **Flexibility** - Skills and Tools from any existing OpenAPI, MCP server, databases, fsspec paths, Python functions
## Key Features
Specify *what* is expected of an agent
Create tools from existing APIs and databases
Create skills to codify *how* to do things
Run your agent
## Quick Example
```bash theme={null}
pip install a1-compiler
```
```python theme={null}
from a1 import Agent, tool, LLM
from pydantic import BaseModel
@tool
async def add(a: int, b: int) -> int:
return a + b
class MathInput(BaseModel):
problem: str
class MathOutput(BaseModel):
answer: int
agent = Agent(
name="math_agent",
description="Solves simple math problems",
input_schema=MathInput,
output_schema=MathOutput,
tools=[add, LLM("gpt-4.1")],
)
# Compile ahead-of-time
compiled = await agent.aot()
result = await compiled.execute(problem="What is 2 + 2?")
# Or execute just-in-time
result = await agent.jit(problem="What is 5 + 3?")
```
## Get Started
Set up A1 in your environment
Build your first agent
Learn about AOT vs JIT
Explore the full API